Yi Gao, Wei Dong, Chun Chen, Jiajun Bu, Tianyu Chen, Mingyuan Xia, Xue Liu, Xianghua Xu
{"title":"Domo: Passive Per-Packet Delay Tomography in Wireless Ad-hoc Networks","authors":"Yi Gao, Wei Dong, Chun Chen, Jiajun Bu, Tianyu Chen, Mingyuan Xia, Xue Liu, Xianghua Xu","doi":"10.1109/ICDCS.2014.50","DOIUrl":null,"url":null,"abstract":"In multi-hop wireless ad-hoc networks, packet delivery delay is one of the most important performance metrics. While a lot of research efforts have been spent on measuring and optimizing the end-to-end delay performance, there usually lack accurate and lightweight methods for decomposing the end-to-end delay into the per-hop delay for each packet. Knowledge on the per-hop per-packet delay can greatly improve the network visibility and facilitate network measurement and management. In this paper, we propose Domo, a passive, lightweight and accurate delay tomography approach to decomposing the packet end-to-end delay into each hop. The basic idea is to formulate the problem into a set of optimization problems by carefully considering the constraints among various timing quantities. At the network side, Domo attaches a small overhead to each packet for constructing constraints of the optimization problems. At the PC side, Domo employs semi-definite relaxation and several other methods to efficiently solve the optimization problems. We implement Domo and evaluate its performance extensively using large-scale simulations. Results show that Domo significantly outperforms two existing methods, nearly tripling the accuracy of the state-of-the-art.","PeriodicalId":170186,"journal":{"name":"2014 IEEE 34th International Conference on Distributed Computing Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 34th International Conference on Distributed Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCS.2014.50","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
In multi-hop wireless ad-hoc networks, packet delivery delay is one of the most important performance metrics. While a lot of research efforts have been spent on measuring and optimizing the end-to-end delay performance, there usually lack accurate and lightweight methods for decomposing the end-to-end delay into the per-hop delay for each packet. Knowledge on the per-hop per-packet delay can greatly improve the network visibility and facilitate network measurement and management. In this paper, we propose Domo, a passive, lightweight and accurate delay tomography approach to decomposing the packet end-to-end delay into each hop. The basic idea is to formulate the problem into a set of optimization problems by carefully considering the constraints among various timing quantities. At the network side, Domo attaches a small overhead to each packet for constructing constraints of the optimization problems. At the PC side, Domo employs semi-definite relaxation and several other methods to efficiently solve the optimization problems. We implement Domo and evaluate its performance extensively using large-scale simulations. Results show that Domo significantly outperforms two existing methods, nearly tripling the accuracy of the state-of-the-art.